Software and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks
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Updated
Dec 17, 2021 - Python
Software and pre-trained models for automatic photo quality enhancement using Deep Convolutional Networks
This is a resouce list for low light image enhancement
[CVPR 2022 Oral] Official repository for "MAXIM: Multi-Axis MLP for Image Processing". SOTA for denoising, deblurring, deraining, dehazing, and enhancement.
Learning Image-adaptive 3D Lookup Tables for High Performance Photo Enhancement in Real-time
Image Upscaling in Javascript. Increase image resolution up to 4x using Tensorflow.js.
A Collection of Papers and Codes for CVPR2021/CVPR2020 Low Level Vision
[ECCV 2020] Learning Enriched Features for Real Image Restoration and Enhancement. SOTA results for image denoising, super-resolution, and image enhancement.
A Tensorflow implementation of RetinexNet
A PyTorch Implementation of Neural IMage Assessment
Several image/video enhancement methods, implemented by Java, to tackle common tasks, like dehazing, denoising, backscatter removal, low illuminance enhancement, featuring, smoothing and etc.
Reference code for the paper: Deep White-Balance Editing (CVPR 2020). Our method is a deep learning multi-task framework for white-balance editing.
Python implementation of "A New Image Contrast Enhancement Algorithm Using Exposure Fusion Framework", CAIP2017
Project page of the paper "Learning Multi-Scale Photo Exposure Correction" (CVPR 2021).
Fast underwater image enhancement for Improved Visual Perception. #TensorFlow #PyTorch #RAL2020
Generating RGB photos from RAW image files with PyNET
Generating RGB photos from RAW image files with PyNET (PyTorch)
A real-time upscaling software that can upscale any application or game window. Forked from Blinue/Magpie, with the intention of maintaining Visual Novel specific presets.
Artificial Intelligence Learning Notes.
White balance camera-rendered sRGB images (CVPR 2019) [Matlab & Python]
Learning a Deep Single Image Contrast Enhancer from Multi-Exposure Images (TIP 2018)
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